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This study aims to propose a novel viscoelastic–viscoplastic combined constitutive model for glassy amorphous polymers within the framework of thermodynamics at finite strain that is capable of capturing their rate-dependent inelastic mechanical behavior in wide ranges of deformation rate and amount.

The rheology model whose viscoelastic and viscoplastic elements are connected in series is set in accordance with the multi-mechanism theory. Then, the constitutive functions are formulated on the basis of the multiplicative decomposition of the deformation gradient implicated by the rheology model within the framework of thermodynamics. Dynamic mechanical analysis (DMA) and loading/unloading/no-load tests for polycarbonate (PC) are conducted to identify the material parameters and demonstrate the capability of the proposed model.

The performance was validated in comparison with the series of the test results with different rates and amounts of deformation before unloading together. It has been confirmed that the proposed model can accommodate various material behaviors empirically observed, such as rate-dependent elasticity, elastic hysteresis, strain softening, orientation hardening and strain recovery.

This paper presents a novel rheological constitutive model in which the viscoelastic element connected in series with the viscoplastic one exclusively represents the elastic behavior, and each material response is formulated according to the multiplicatively decomposed deformation gradients. In particular, the yield strength followed by the isotropic hardening reflects the relaxation characteristics in the viscoelastic constitutive functions so that the glass transition temperature could be variant within the wide range of deformation rate. Consequently, the model enables us to properly represent the loading process up to large deformation regime followed by unloading and no-load processes.

This study aims to investigate the compression characteristics of the 3D-printed polylactic acid (PLA) samples at temperatures below the glass transition temperature (T_g) with varying strain rates and develop a thermo-mechanical viscoplastic constitutive model to predict the finite strain compression response using a single set of material parameters. Also, the micro-mechanical damage processes are linked to the global stress–strain response at varied strain rates and temperatures through scanning electron microscopy (SEM).

T_g of PLA was determined using a dynamic mechanical analyzer. Compression experiments were conducted at strain rates of 2 × 10^–3/s and 2 × 10^–2/s at 25°C, 40°C and 50°C. The failure mechanisms were examined using SEM. A finite strain thermo-mechanical viscoplastic constitutive model was developed to analyze the deformations at the considered strain rates and temperatures.

T_g of PLA was determined as 55°C. While the yield and post-yield stresses drop with increasing temperature, their trend reverses with an increased strain rate. SEM imaging indicated plasticizing effects at higher temperatures, while filament fragmentation and twisting at higher strain rates were identified as the dominant failure mechanisms. Using a non-linear regression analysis to predict the experimental data, an overall R² value of 0.98 was achieved between experimental and model prediction, implying the robustness of the model’s calibration.

In this study, a viscoplastic constitutive model was developed that considers the combined effect of temperature and strain rate for FDM-printed PLA experiencing extensive compression. Using appropriate temperature-dependent modulus and flow rate properties, a single set of model parameters predicted the rise in the gap between yield stress and degree of softening as strain rates and temperatures increased.

The purpose of this paper is to develop and parameterize a time‐invariant (equilibrium) material mechanical model for segmented polyureas, a class of thermoplastically linked co‐polymeric elastomers, using experimental data available in open literature.

The key components of the model are developed by first constructing a simple molecular‐level microstructure model and by relating the microstructural elements and intrinsic material processes to the material mechanical response. The new feature of the present material model relative to the ones currently used is that the physical origin and the evolution equation for the deformation‐induced softening and inelasticity observed in polyureas are directly linked to the associated evolution of the soft‐matrix/hard segment molecular‐level microstructure of this material. The model is first developed for the case of uniaxial loading, parameterized using one set of experimental results and finally validated using another set of experimental results.

The validation procedure suggested that the model can reasonably well account for the equilibrium mechanical response of polyureas under the simple uniaxial loading conditions.

The present approach enables a more accurate determination of the mechanical behavior of polyurea and related elastomeric materials.

The purpose of this study is to experimentally investigate the large deformation compression characteristics of fused deposition modelling (FDM)-printed poly lactic acid (PLA), considering the combined effect of infill density and strain rate, and to develop a constitutive viscoplastic model that can incorporate the infill density to predict the experimental result.

The experimental approach focuses on strain rate-dependent (2.1 × 10⁻⁴, 2.1 × 10⁻³, and 2.1 × 10⁻² s⁻¹) compression testing for varied infill densities. Scanning electron microscopy (SEM) imaging of compressed materials is used to investigate deformation processes. A hyperelastic-viscoplastic constitutive model is constructed that can predict mechanical deformations at different strain rates and infill densities.

The yield stress of PLA increased with increase in strain rate and infill density. However, higher degree of strain-softening response was witnessed for the strain rate corresponding to 2.1 × 10⁻² s⁻¹. While filament splitting and twisting were identified as the damage mechanisms at higher strain rates, matrix crazing was observed as the primary deformation mechanism for higher infill density (95%). The developed constitutive model captured yield stress and post-yield softening behaviour of FDM build PLA samples with a high R² value of 0.99.

This paper addresses the need to analyse and predict the mechanical response of FDM print polymers (PLA) undergoing extensive strain-compressive loading through a hyperelastic-viscoplastic constitutive model. This study links combined effects of the printing parameter (infill density) with the experimental parameter (strain rate).

A new and explicit form of the elastic strain-energy function for modeling large strain elastic responses of soft solids is constructed based on Hencky's logarithmic strain tensor.

Well-designed invariants of the Hencky strain are introduced for characterizing deformation modes and, furthermore, a new interpolating technique is proposed for combining piecewise splines into a single smooth function.

With this new form and this new technique, objectives in three respects may be achieved for the first time.

First, no adjustable parameters need to be treated. Second, large strain responses for three benchmark modes are derivable in a decoupled sense without involving strongly nonlinear coupling effects. Finally, large strain data may be automatically and accurately matched for three benchmark modes, including uniaxial, equi-biaxial and plane-strain extension. Numerical examples are presented and compared with usual approaches.

The stories told in organizations offer researchers and organizational development practitioners a natural entry point to understanding and intervening in the culture(s) of an organization. Informed by perspectives of social constructivism, organizational symbolism, and critical theory, examines key studies of organizational story and storytelling, identifies multidisciplinary foundations, and presents challenges to the application of story work in organizations.

This chapter explores Prospect Theory — a descriptive model of modelling individual choice making under risk and uncertainty, and its applications to a range of travel behaviour contexts.

The chapter provides background on Prospect Theory, its basic assumptions and formulations, and summarises some of its theoretical developments, applications and evidence in the field of transport research.

A body of empirical evidence has accumulated showing that the principle of maximisation of expected utility provides limited explanation of travel choices under risk and uncertainty. Prospect Theory can be seen as an alternative and promising framework for travel choice modelling (although not without theoretical and practical controversy). These findings are supported by empirical observations reported in the literature reviewed in this chapter.

The chapter provides a detailed account of the design and results of accumulated research in travel behaviour research that is based on Prospect Theory’s observations, insights and formulations. The potential of Prospect Theory for particular decision-making in travel behaviour research is articulated, main findings are presented and discussed, and limitations are identified, leading to further research needs.

This work presents a review of the application of hyperelastic models to the analysis of fabrics using finite element analysis (FEA).

In general, a combination of uniaxial tension (compression), biaxial tension, and simple shear is required for the characterization of a hyperelastic material. However, the use of these deformation tests to obtain the mechanical properties of a fabric may be complicated and also expensive. A methodology for characterizing the fabric employing a different experimental test is presented. The methodology consists of a comparison of the results of the fabric characterization with only a tensile test and the combination of shear, biaxial, and tension experimental tests by using FEA.

Numerical results of the fabric behavior contribute to estimate the effects of experimental limitations in the material characterization and to select the best fit material model to modeling fabrics. Finally, a comparison of hyperelastic material models is illustrated through an example of a rigid body in contact with a hyperelastic fabric in 3D.

Hyperelastic models are used to characterize textile materials.

Polyurea is an elastomeric two-phase co-polymer consisting of nanometer-sized discrete hard (i.e. high glass transition temperature) domains distributed randomly within a soft (i.e. low glass transition temperature) matrix. A number of experimental investigations reported in the open literature clearly demonstrated that the use of polyurea external coatings and/or internal linings can significantly increase blast survivability and ballistic penetration resistance of target structures, such as vehicles, buildings and field/laboratory test-plates. When designing blast/ballistic-threat survivable polyurea-coated structures, advanced computational methods and tools are being increasingly utilized. A critical aspect of this computational approach is the availability of physically based, high-fidelity polyurea material models. The paper aims to discuss these issues.

In the present work, an attempt is made to develop a material model for polyurea which will include the effects of soft-matrix chain-segment molecular weight and the extent and morphology of hard-domain nano-segregation. Since these aspects of polyurea microstructure can be controlled through the selection of polyurea chemistry and synthesis conditions, and the present material model enables the prediction of polyurea blast-mitigation capacity and ballistic resistance, the model offers the potential for the “material-by-design” approach.

The model is validated by comparing its predictions with the corresponding experimental data.

The work clearly demonstrated that, in order to maximize shock-mitigation effects offered by polyurea, chemistry and processing/synthesis route of this material should be optimized.